Known
AI / ML Engineer
San Francisco, CA
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- Role family
- Data & ML
- Seniority
- Mid level
- Country
- US
- Work mode
- On-site / unstated
- First seen by hirly
- 1 Sept 2026
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the posting
Known - Founding Machine Learning Engineer
San Francisco, CA (In-Person)
200k-375k Cash + Equity
Known is a matchmaker that talks to users and supports them like a friend. Our mission is to empower humanity by applying general intelligence to human connection.
Users join Known by telling us their life story. On average, our new users talk to our AI voice agent for 27 minutes , giving us a uniquely intimate multi-modal data set.
We are a team of engineers who’ve created some of the most widely used AI-driven consumer products including Uber Eats , Uber, Faire and Afterpay .
We love to work hard, with a high degree of autonomy and ownership. We work together in Cow Hollow, San Francisco.
Learn more
Known
Our Launch
Known’s 10M Seed | TechCrunch
“You Don’t Need to Swipe Right” - Known | NYT
Known | FastCompany
Website
About the Role
We’re looking for founding machine learning engineers to continue to design and build Known’s core systems intelligence, driving our recommendation engine and agentic systems.
This is a unique opportunity to work with an ultra-personal data-set, combining voice transcripts, images, and structured user data to create both personalized AI companions as well as predict human compatibility. You’ll work directly with Chen Peng, former head of ML at Uber Eats and Faire.
What you’ll do
It’s up to you to decide what part of the ML stack you’re most excited about working on.
This could be :
Training and deploying ML models that form the core of our recommendation engine
Designing evals to assess recommendation ability and RL systems to learn from results data
Building personalization and long-term memory systems into Known’s conversational AI
Using LLMs to enhance our suite of user facing AI Agents
You will own the end-to-end lifecycle of your models, from ideation and training to deployment and monitoring.
Requirements
4-6 years experience training and deploying ML models in production, leveraging PyTorch and TensorFlow
Applying or fine-tuning LLMs to build agentic systems or complex conversational AI
Experience with neural network models
Experience with model deployment and basic infrastructure (e.g., Docker, Kubernetes, AWS/GCP)
You want to build intelligence that could lead to a million marriages and babies
Our Investors
We’re backed by Eurie Kim and Kirsten Green at Forerunner Ventures (the investors behind Decagon, Faire, and Oura), NFX and PearVC.
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